Multimodal deep learning for allergenic proteins prediction by Lezheng Yu, Yuxin Luo, Shiqi Wu, Siyi Chen, Li Xue, Runyu Jing, Jiesi Luo

“…Results Here, we present Multimodal-AlgPro, a unified framework based on a multimodal deep learning algorithm designed to predict allergens by integrating multiple dimensions, including physicochemical properties, amino acid sequences, and evolutionary information. …”
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Prediction of Drifter Trajectory Using Evolutionary Computation by Yong-Wook Nam, Yong-Hyuk Kim

“…In contrast to existing numerical models that use the Lagrangian method, we used an optimization algorithm to predict the trajectory. As the evaluation measure, a method that gives a better score as the Mean Absolute Error (MAE) when the difference between the predicted position in time and the actual position is lower and the Normalized Cumulative Lagrangian Separation (NCLS), which is widely used as a trajectory evaluation method of drifters, were used. …”
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Machine Learning with Voting Committee for Frost Prediction by Vinícius Albuquerque de Almeida, Juliana Aparecida Anochi, José Roberto Rozante, Haroldo Fraga de Campos Velho

“…The AdaBoostClassifier algorithm was employed to implement the voting committee. …”
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Predicting surgical risk in morbidly obese patients by K. A. Anisimova, D. I. Vasilevsky, S. G. Balandov, E. T. Berulava, A. V. Zinchenko, N. V. Markov, I. G. Buhankov, E. V. Blinov, G. V. Semikova

“…The results obtained during the study made it possible to integrate the developed tactics of preoperative examination and preparation for surgical intervention in morbidly obese patients into a practical algorithm. Application of the developed tools for predicting the risk of complications in bariatric surgeries allowed to reduce the complication rate from 12.2 % to 2.0 %, and the mortality rate from 2.0 % to 0 %.CONCLUSION. …”
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Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…Predictive Control optimization often relies on exhaustive enumeration of voltage vectors within the finite control set. …”
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Machine Learning for Health Insurance Prediction in Nigeria by Victor Enemona Ochigbo, Oluwasogo Adekunle Okunade, Emmanuel Gbenga Dada, Oluyemi Mikail Olaniyi, Oluwatoyosi Victoria Oyewande

“…Random Forest is a robust ensemble learning algorithm capable of capturing complex relationships within the data. …”
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Population FBA predicts metabolic phenotypes in yeast. by Piyush Labhsetwar, Marcelo C R Melo, John A Cole, Zaida Luthey-Schulten

“…We use a genetic algorithm to determine the proteomics constraints necessary to reproduce the growth rate distributions seen experimentally. …”
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STEP-BY-STEP PREDICTION OF LATE SPONTANEOUS MISCARRIAGE by Юлия Алексеевна Дударева, Татьяна Викторовна Раченкова, Сергей Вадимович Дронов

“…The aim of the study was to develop a step-by-step system for predicting late spontaneous miscarriages, taking into account clinical, anamnestic, echographic data, and the cytokine status of pregnant women. …”
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AI model for predicting asthma prognosis in children by Elham Sagheb, MS, Chung-Il Wi, MD, Katherine S. King, MS, Bhavani Singh Agnikula Kshatriya, MS, Euijung Ryu, PhD, Hongfang Liu, PhD, Miguel A. Park, MD, Hee Yun Seol, MD, Shauna M. Overgaard, PhD, Deepak K. Sharma, PhD, Young J. Juhn, MD, Sunghwan Sohn, PhD

“…The prediction model at age 12 showed the highest performance. …”
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Prediction models for COVID-19 disease outcomes by Cynthia Y. Tang, Cheng Gao, Kritika Prasai, Tao Li, Shreya Dash, Jane A. McElroy, Jun Hang, Xiu-Feng Wan

“…Using the Virus-Human Outcomes Prediction (ViHOP) algorithm, we aim to utilize the individual’s clinical characteristics, the individual’s location, and the infecting SARS-CoV-2 virus characteristics obtained by whole genome sequencing to determine their likelihood of admission to the hospital, admission to the intensive care unit (ICU), or experiencing long COVID. …”
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HRDA-Net: image multiple manipulation detection and location algorithm in real scene by Ye ZHU, Yilin YU, Yingchun GUO

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Combining the Multi-Genetic Algorithm and Support Vector Machine for Fault Diagnosis of Bearings by Jianbin Xiong, Qinghua Zhang, Qiong Liang, Hongbin Zhu, Haiying Li

“…The algorithm optimizes the correlation kernel parameters of the SVM using evolutionary search principles of multiple swarm genetic algorithms to obtain a superior SVM prediction model. …”
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A Filtering Algorithm for Maneuvering Target Tracking Based on Smoothing Spline Fitting by Yunfeng Liu, Jidong Suo, Hamid Reza Karimi, Xiaoming Liu

“…Monte Carlo simulation results show that, when sea targets are maneuvering, the proposed algorithm has better accuracy than the conventional Kalman filter algorithm and the interactive multiple model filtering algorithm, maintaining simple structure and small amount of storage.…”
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Classification algorithm for imbalance data of ECG based on PSOFS and TSK fuzzy system by Xinhui LI, Qing SHEN, Xiongtao ZHANG

“…., parallel ensemble fuzzy neural network based on PSOFS and TSK (PE-PT-FN), which was used for ECG prediction.Each class sample in the training set was randomly sampled, and the samples obtained by randomly sampled were added.Then, the feature selection method PSOFS was carried out independently and parallelly.In PSOFS, particles that were random initial positions represent different feature subsets and converge to the optimal positions after many iterations.Each subset had a corresponding feature subset.Several groups of TSK fuzzy neural network (TSK-FNN) were trained by each feature subset in parallel.Medical researchers could effectively find the correlation between ECG signal data and different types of disease through the interpretability of the fuzzy system and the feature subsets by the PSOFS algorithm.Experiments prove that PE-PT-FN greatly improves the macro-R to 92.35% while retaining interpretability.…”
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Research on Parameter Extraction Method of Photovoltaic Module Based on Improved Hybrid Algorithm by Haitao Wu, Zhou Shang

“…Firstly, the analytical method is applied to simplify the equivalent circuit model and improve the efficiency of the algorithm. Then, the adaptive algorithm is used to adjust the parameters of the differential evolution algorithm. …”
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Knee Point-Guided Multiobjective Optimization Algorithm for Microgrid Dynamic Energy Management by Wenhua Li, Guo Zhang, Tao Zhang, Shengjun Huang

“…Model predictive control (MPC) technology can effectively reduce the bad effect caused by inaccurate data prediction in microgrid energy management problem. …”
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Recognizing Cow Muzzle Patterns using the Convolution Neural Network (CNN) Algorithm by Sulthon Zamroni, Giri Wahyu Wiriasto, Bulkis Kanata

“…Numerous systems and algorithms have been developed to recognize cattle, ranging from body shape, fur patterns, to specific parts of the cattle. …”
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Bayesian Robust Tensor Decomposition Based on MCMC Algorithm for Traffic Data Completion by Longsheng Huang, Yu Zhu, Hanzeng Shao, Lei Tang, Yun Zhu, Gaohang Yu

“…In this paper, a Bayesian robust tensor decomposition method (MBRTF) based on the Markov chain Monte Carlo (MCMC) algorithm is proposed. The underlying low CANDECOMP/PARAFAC (CP) rank tensor captures the global information, and the sparse tensor captures local information (also regarded as anomalous data), which achieves a reliable prediction of missing terms. …”
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A Collaborative Filtering Recommendation Algorithm Based on User Confidence and Time Context by Guangxia Xu, Zhijing Tang, Chuang Ma, Yanbing Liu, Mahmoud Daneshmand

“…Finally, the experimental results demonstrate that the proposed algorithm is suitable for the sparse data and effectively improves the prediction accuracy and enhances the recommendation quality at the same time.…”
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Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm by Methaq Hadi Lafta

“…So this research is trying to provide a method based on LQG controller with and then set motion and specify path scheduling without deviations based on swarm intelligence algorithms in combinational mode: Dragonfly-Firefly algorithm. …”
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